#!/usr/bin/env python # -*- coding: utf-8 -*- ''' ################################################## ## TOML CALIBRATION TO QCA CALIBRATION ## ################################################## Convert an OpenCV .toml calibration file to a Qualisys .qca.txt calibration file Usage: from Pose2Sim.Utilities import calib_toml_to_qca; calib_toml_to_qca.calib_toml_to_qca_func(r'') OR python -m calib_toml_to_qca -i input_toml_file OR python -m calib_toml_to_qca -i input_toml_file --binning_factor 2 --pixel_size 5.54e-3 -o output_qca_file ''' ## INIT import os import argparse import numpy as np import toml from lxml import etree import cv2 ## AUTHORSHIP INFORMATION __author__ = "David Pagnon" __copyright__ = "Copyright 2021, Pose2Sim" __credits__ = ["David Pagnon"] __license__ = "BSD 3-Clause License" __version__ = '0.4' __maintainer__ = "David Pagnon" __email__ = "contact@david-pagnon.com" __status__ = "Development" ## FUNCTIONS def read_toml(toml_path): ''' Read an OpenCV .toml calibration file Returns 5 lists of size N (N=number of cameras): - S (image size), - D (distorsion), - K (intrinsic parameters), - R (extrinsic rotation), - T (extrinsic translation) ''' calib = toml.load(toml_path) C, S, D, K, R, T = [], [], [], [], [], [] for cam in list(calib.keys()): if cam != 'metadata': C += [calib[cam]['name']] S += [np.array(calib[cam]['size'])] D += [np.array(calib[cam]['distortions'])] K += [np.array(calib[cam]['matrix'])] R += [np.array(calib[cam]['rotation'])] T += [np.array(calib[cam]['translation'])] return C, S, D, K, R, T def world_to_camera_persp(r, t): ''' Converts rotation R and translation T from Qualisys object centered perspective to OpenCV camera centered perspective and inversely. Qc = RQ+T --> Q = R-1.Qc - R-1.T ''' r = r.T t = - r.dot(t) return r, t def rotate_cam(r, t, ang_x=np.pi, ang_y=0, ang_z=0): ''' Apply rotations around x, y, z in cameras coordinates ''' rt_h = np.block([[r,t.reshape(3,1)], [np.zeros(3), 1 ]]) r_ax_x = np.array([1,0,0, 0,np.cos(ang_x),-np.sin(ang_x), 0,np.sin(ang_x),np.cos(ang_x)]).reshape(3,3) r_ax_y = np.array([np.cos(ang_y),0,np.sin(ang_y), 0,1,0, -np.sin(ang_y),0,np.cos(ang_y)]).reshape(3,3) r_ax_z = np.array([np.cos(ang_z),-np.sin(ang_z),0, np.sin(ang_z),np.cos(ang_z),0, 0,0,1]).reshape(3,3) r_ax = r_ax_z.dot(r_ax_y).dot(r_ax_x) r_ax_h = np.block([[r_ax,np.zeros(3).reshape(3,1)], [np.zeros(3), 1]]) r_ax_h__rt_h = r_ax_h.dot(rt_h) r = r_ax_h__rt_h[:3,:3] t = r_ax_h__rt_h[:3,3] return r, t def qca_write(qca_path, C, S, D, K, R, T, binning_factor, pixel_size): ''' Writes calibration parameters to a .qca.txt file. ''' # OpenCV to Qualisys variables conversions S = [[int(ss*binning_factor) for ss in s] for s in S] R = [r.T for r in R] fm = [k[0,0]*binning_factor*pixel_size for k in K] K = [k*binning_factor*64 for k in K] D = [d*binning_factor*64 for d in D] # .qca.txt construction root = etree.Element('calibration', source=os.path.basename(qca_path), created='sometimes ago', qtmversion='none', type='regular', wandLength='none', maximumFrames="none", shortArmEnd="none", longArmEnd="none", longArmMiddle="none") etree.SubElement(root, 'results', stddev='0.', minmaxdiff='0.') cams = etree.SubElement(root, 'cameras') for c in range(len(C)): cam = etree.SubElement(cams, 'camera', active='1', pointcount='999999999', avgresidual='0.', serial=C[c], model='none', viewrotation='0') etree.SubElement(cam, 'fov_marker', left='0', top='0', right=str(S[c][0]), bottom=str(S[c][1])) etree.SubElement(cam, 'fov_marker_max', left='0', top='0', right=str(S[c][0]), bottom=str(S[c][1])) etree.SubElement(cam, 'fov_video', left='0', top='0', right=str(S[c][0]), bottom=str(S[c][1])) etree.SubElement(cam, 'fov_video_max', left='0', top='0', right=str(S[c][0]), bottom=str(S[c][1])) etree.SubElement(cam, 'transform', x=str(T[c][0]), y=str(T[c][1]), z=str(T[c][2]), r11=str(R[c][0,0]), r12=str(R[c][0,1]), r13=str(R[c][0,2]), r21=str(R[c][1,0]), r22=str(R[c][1,1]), r23=str(R[c][1,2]), r31=str(R[c][2,0]), r32=str(R[c][2,1]), r33=str(R[c][2,2])) etree.SubElement(cam, 'intrinsic', focallength=str(fm[c]), sensorMinU='0.000000', sensorMaxU=str(S[c][0]*64), sensorMinV='0.000000', sensorMaxV=str(S[c][1]*64), focalLengthU=str(K[c][0,0]), focalLengthV=str(K[c][1,1]), centerPointU=str(K[c][0,2]), centerPointV=str(K[c][1,2]), skew='0.000000', radialDistortion1=str(D[c][0]), radialDistortion2=str(D[c][1]), radialDistortion3='0.000000', tangentalDistortion1=str(D[c][2]), tangentalDistortion2=str(D[c][3])) etree.ElementTree(root).write(qca_path, xml_declaration=True, pretty_print=True) # python XML file: had to delete hyphens in qtm-version, std-dev, min-max-diff, point-count, avg-residual' -> Replace them now with open(qca_path, 'r') as f: sample1 = f.read().replace('qtmversion', 'qtm-version', 1) sample2 = sample1.replace('stddev', 'std-dev', 1) sample3 = sample2.replace('minmaxdiff', 'min-max-diff', 1) sample4 = sample3.replace('pointcount', 'point-count') sample5 = sample4.replace('avgresidual', 'avg-residual') with open(qca_path, 'w') as f: f.write(sample5) def calib_toml_to_qca_func(**args): ''' Convert an OpenCV .toml calibration file to a Qualisys .qca.txt calibration file Usage: import calib_toml_to_qca; calib_toml_to_qca.calib_toml_to_qca_func(input_file=r'') OR calib_toml_to_qca -i input_toml_file OR calib_toml_to_qca -i input_toml_file --binning_factor 2 --pixel_size 5.54e-3 -o output_qca_file ''' toml_path = args.get('input_file') qca_path = args.get('output_file') if qca_path == None: qca_path = toml_path.replace('.toml', '.qca.txt') binning_factor = args.get('binning_factor') if binning_factor == None: binning_factor = 1 binning_factor = int(binning_factor) pixel_size = args.get('pixel_size') if pixel_size == None: pixel_size = 5.54e-3 pixel_size = float(pixel_size) C, S, D, K, R, T = read_toml(toml_path) R = [np.array(cv2.Rodrigues(r)[0]) for r in R] T = np.array(T) * 1000 RT = [rotate_cam(r, t, ang_x=np.pi, ang_y=0, ang_z=0) for r, t in zip(R, T)] R = [rt[0] for rt in RT] T = [rt[1] for rt in RT] RT = [world_to_camera_persp(r,t) for r, t in zip(R, T)] R = [rt[0] for rt in RT] T = [rt[1] for rt in RT] qca_write(qca_path, C, S, D, K, R, T, binning_factor, pixel_size) print('Calibration file generated.\n') if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-i', '--input_file', required = True, help='OpenCV .toml output calibration file') parser.add_argument('-b', '--binning_factor', required = False, default = 1, help='Binning factor if applied') parser.add_argument('-p', '--pixel_size', required = False, default = 5.54e-3, help='Pixel size in mm, 5.54e-3 mm by default (CMOS CMV2000)') parser.add_argument('-o', '--output_file', required=False, help='Qualisys .qca.txt input calibration file') args = vars(parser.parse_args()) calib_toml_to_qca_func(**args)